Triple
T10100487
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Blue Island–Vermont Street station |
E216185
|
entity |
| Predicate | distanceFromChicagoLaSalleStreetStation |
P92431
|
FINISHED |
| Object | approximately 16.4 miles |
—
|
LITERAL FINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: approximately 16.4 miles | Statement: [Blue Island–Vermont Street station, distanceFromChicagoLaSalleStreetStation, approximately 16.4 miles]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceFromChicagoLaSalleStreetStation Context triple: [Blue Island–Vermont Street station, distanceFromChicagoLaSalleStreetStation, approximately 16.4 miles]
-
A.
distanceFromChicagoUnionStation
Indicates the measured distance between a given location and Chicago Union Station.
-
B.
distanceFromChicagoLoop
Indicates the spatial distance between an entity’s location and the Chicago Loop area.
-
C.
distanceToChicagoLoop
Indicates the spatial distance between a given location and Chicago’s central business district (the Loop).
-
D.
distanceFromChampaign
Indicates the measured distance between a given entity’s location and the location of Champaign.
-
E.
distanceFromUrbana
Indicates the measured spatial distance between a given entity or location and Urbana.
- F. None of above. chosen
Provenance (4 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69ca83d039f08190b9d10363221c69fb |
completed | March 30, 2026, 2:08 p.m. |
| NER | Named-entity recognition | batch_69cdd09878f88190bcfa2c81fb10e821 |
completed | April 2, 2026, 2:12 a.m. |
| PD | Predicate disambiguation | batch_69cd4b9b853c8190a2af993ce9b21309 |
completed | April 1, 2026, 4:45 p.m. |
| PDg | Predicate description generation | batch_69cd5150ae98819086c4f822114b4e2c |
completed | April 1, 2026, 5:09 p.m. |
Created at: March 30, 2026, 9:02 p.m.